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All Journal EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Pseudocode Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Jurnal Informatika dan Teknik Elektro Terapan agriTECH Jurnal Kreativitas PKM Barometer International Journal of Aviation Science and Engineering International Journal of Electronics and Communications Systems Jurnal Inovasi Pembangunan Journal of Applied Science, Engineering and Technology (J. ASET) Malcom: Indonesian Journal of Machine Learning and Computer Science Seminar Nasional Insinyur Profesional (SNIP) Prosiding Seminar Nasional Hasil Penelitian Sains, Teknik dan Aplikasi Industri Fakultas Teknik Universitas Lampung Electrician : Jurnal Rekayasa dan Teknologi Elektro Jurnal Teknologi Riset Terapan Nemui Nyimah
Mulyani, Yessi
Universitas Lampung
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Journal : International Journal of Electronics and Communications Systems

 1 
Comparison Study of Convolutional Neural Network Architecture in Aglaonema Classification Mulyani, Yessi; Septiangraini, Dzihan; Muhammad, Meizano Ardhi; Nama, Gigih Forda
International Journal of Electronics and Communications Systems Vol. 2 No. 2 (2022): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v2i2.13694

Abstract

Convolutional Neural Network (CNN) is very good at classifying images. To measure the best CNN architecture, a study must be done against real-case scenarios. Aglaonema, one of the plants with high similarity, is chosen as a test case to compare CNN architecture. In this study, a classification process was carried out on five classes of Aglaonema imagery by comparing five architectures from the Convolutional Neural Network (CNN) method: LeNet, AlexNet, VGG16, Inception V3, and ResNet50. The total dataset used is 500 image data, with the distribution of training data by 80 percent and test data by 20 percent. The segmentation process is performed using the Grabcut algorithm by separating the foreground and background. To build a model for CNN architecture using Google Colab and Google Drive storage. The results of the tests carried out on five classes of Aglaonema images obtained the best accuracy, precision, and recall results on the Inception V3 architecture with values of 92.8 percent, 93 percent, and 92.8 percent. The CNN architecture has the highest level of accuracy in classifying aglaonema plant types based on images. This study seeks to close research gaps, contribute to the field of research, and serve as a platform for primary prevention research.
Development of Lampung Script Characters Recognition Model using TensorFlow Muhammad, Meizano Ardhi; Martinus, Martinus; Nurhartanto, Adhi; Mulyani, Yessi; Djausal, Gita Paramita; Achmad, Deni; Ferbangkara, Sony
International Journal of Electronics and Communications Systems Vol. 3 No. 2 (2023): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v3i2.19878

Abstract

In the face of cultural erosion, particularly the dwindling proficiency in deciphering Lampung characters, this research pioneers an innovative approach to cultural preservation. The Lampung character recognition model was developed using TensorFlow, a robust computer vision and machine learning framework. Convolutional Neural Networks (CNN) are integrated to enhance the image processing capabilities. The research employs the Design Science Research methodology, emphasizing problem identification, solution objectives, design and development, demonstration, evaluation, and communication. The dataset, comprising 3900 instances, is meticulously collected and features diverse Lampung script writing. Through preprocessing and classification, the model undergoes training with an 80:10:10 split for training, validation, and test data. The architecture includes CNN layers with ReLu activation functions, and transfer learning is employed using the MobileNet V2 network model. Demonstrating commendable performance, the model achieves an accuracy spectrum of 0.652 to 0.998. The research not only underscores the viability of the TensorFlow model but also establishes a foundation for future explorations in preserving Lampung cultural heritage. This intersection of advanced machine learning and cultural preservation signifies a promising synergy, ensuring the enduring legacy of Lampung characters amid societal and technological transformations.
Co-Authors Adhi Nurhartanto, Adhi Ageng Sadnowo Repelianto Agus Haryanto Agustina, Indria Ardi Ragil Saputra Arifudin, M. Bagus br Ginting, Simparmin Budi Wintoro, Puput Cahyana, Amanda Hasna Deni Achmad Djausal, Gita Paramita Dzihan Septiangraini Efendi, Ujang Eliza Hara Fajriansyah, Gilang Filya, Kwinny Intan Gigih Forda Nama Gilang Fajriansyah Gita Paramitha Djausal Gunawan, Charles Gusti, Khalid Surya Halim Abdillah Sholeh Helmy Fitriawan Herti Utami Hery Dian Saptama Hery Dian Septama Hery Dian Septama Hilmi Hermawan Huda, Zulmiftah Ilim, Ilim Irza Sukmana Jaya, Winaldi Putra Kesuma, Yunita Khalid Surya Gusti Komarudin, M. Laksana, Muhammad Fajar lina marlina, lina M. Bagus Arifudin Mahendra Pratama MARDIANA Mardiana Mardiana Mareli Telaumbanua Martinus Martinus Martinus, Martinus Meizano Ardhi Muhammad Meizano Ardi Muhamad Mona Arif Muda Mugahed Al-Rahmi, Waleed Muhamad Komarudin Muhamad Komarudin Muhamad Komarudin Muhammad Amin Muhammad Komarudin Muhammad Komarudin Muhammad, Meizano Ardhi Nanda Sazqiah Nyoman Herman Ardike Panji Kurniawa Pratama, Rama Wahyu Ajie Puput budi wintoro Puput Budi Wintoro Puput Budi Wintoro, Puput Budi Putri, Renatha Amelia Manggala Rafi'syaiim, Muhammad Afif Ragil Saputra, Ardi Reza Dwi Permana Rhomadhona, Nazmah Wulan Rian Kurniawan Rian Kurniawan Satrio, Muhamad Septiangraini, Dzihan Shalihah , Atiqah Hanifah Sony Ferbangkara Sugeng Triyono Titin Yulianti Trisya Septiana Umi Murdika Wahyu Aji Pulungan Wahyu Eko Sulistiono Waleed Mugahed Al-Rahmi Wijaya , Aldo Wulan Rahma Izzati